A survey of Internet users reported that 15% downloaded music onto their compute
ID: 3152974 • Letter: A
Question
A survey of Internet users reported that 15% downloaded music onto their computers. The filing of lawsuits by the recording industry may be a reason why this percent has decreased from the estimate of 25% from a survey taken two years before. Suppose we are not exactly sure about the sizes of the samples. Perform the calculations for the significance tests and 95% confidence intervals under each of the following assumptions. (Use previous recent. Round your test statistics to two decimal places and your confidence intervals to four decimal places.)
(i) Both sample sizes are 1000.
z=
95% C.I.=
(ii) Both sample sizes are 1600.
z=
95% C.I.=
(iii) The sample size for the survey reporting 25% is 1000 and the sample size for the survey reporting 15% is 1600.
z=
95% C.I.=
Summarize the effects of the sample sizes on the results.
We see in (i) and (ii) that smaller samples result in larger z (stronger evidence) and narrower intervals, while larger samples have the reverse effect. The results of (iii) show that the effect of varying unequal sample sizes is more complicated.
We see in (i) and (ii) that smaller samples result in smaller z (weaker evidence) and wider intervals, while larger samples have the reverse effect. The results of (iii) show that the effect of varying unequal sample sizes is more complicated.
We see in (i) and (ii) that smaller samples result in larger z (weaker evidence) and smaller intervals, while larger samples have the reverse effect. The results of (iii) show that the effect of varying unequal sample sizes is more complicated.
We see in (i) and (ii) that smaller samples result in smaller z (stronger evidence) and wider intervals, while larger samples have the reverse effect. The results of (iii) show that the effect of varying unequal sample sizes is more complicated.
We see in (i) and (ii) that smaller samples result in smaller z (weaker evidence) and narrower intervals, while larger samples have the reverse effect. The results of (iii) show that the effect of varying unequal sample sizes is more complicated.
Explanation / Answer
i.
Formulating the hypotheses
Ho: p1 - p2 = 0
Ha: p1 - p2 =/= 0
Here, we see that pdo = 0 , the hypothesized population proportion difference.
Getting p1^ and p2^,
p1^ = x1/n1 = 0.15
p2 = x2/n2 = 0.25
Also, the standard error of the difference is
sd = sqrt[ p1 (1 - p1) / n1 + p2 (1 - p2) / n2] = 0.017748239
Thus,
z = [p1 - p2 - pdo]/sd = -5.634361698 [ANSWER, Z]
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For the 95% confidence level, then
alpha/2 = (1 - confidence level)/2 = 0.025
z(alpha/2) = 1.959963985
Margin of error = z(alpha/2)*sd = 0.03478591
lower bound = p1^ - p2^ - z(alpha/2) * sd = -0.13478591
upper bound = p1^ - p2^ + z(alpha/2) * sd = -0.06521409
Thus, the confidence interval is
( -0.13478591 , -0.06521409 ) [ANSWER, CI]
*****************************************************
ii.
Formulating the hypotheses
Ho: p1 - p2 = 0
Ha: p1 - p2 =/= 0
Here, we see that pdo = 0 , the hypothesized population proportion difference.
Getting p1^ and p2^,
p1^ = x1/n1 = 0.15
p2 = x2/n2 = 0.25
Also, the standard error of the difference is
sd = sqrt[ p1 (1 - p1) / n1 + p2 (1 - p2) / n2] = 0.014031215
Thus,
z = [p1 - p2 - pdo]/sd = -7.126966451 [ANSWER, Z]
**********************
For the 95% confidence level, then
alpha/2 = (1 - confidence level)/2 = 0.025
z(alpha/2) = 1.959963985
Margin of error = z(alpha/2)*sd = 0.027500676
lower bound = p1^ - p2^ - z(alpha/2) * sd = -0.127500676
upper bound = p1^ - p2^ + z(alpha/2) * sd = -0.072499324
Thus, the confidence interval is
( -0.127500676 , -0.072499324 ) [ANSWER, CI]
****************************************************
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